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Duration 14 hours
Course Outline
Azure Machine Learning Fundamentals
- Overview of AML features and architecture
- Introduction to end-to-end workflows in AML (Azure ML pipelines)
- Navigating the Azure Machine Learning Studio interface
Data Preparation and Modeling
- Techniques for data preparation
- Constructing machine learning models
- Processes for training and testing models
Model Evaluation and Robustness
- Utilizing validation metrics for ML models
- Strategies for handling and preventing overfitting
Model Management and Deployment
- Registering trained models
- Creating model images
- Deploying models to production environments
OpenAI API Basics on Azure
- Introduction to the OpenAI API capabilities
- API configuration and authentication methods
Retrieval and Application Integration
- Working with documents using AI Search
- Integrating OpenAI models into application architectures
Customization and Production Practices
- Techniques for model fine-tuning and customization
- Best practices for production deployment
Summary and Next Steps
Requirements
- A solid grasp of Python and fundamental machine learning concepts
- Practical experience working with REST APIs or SDKs
- Basic familiarity with core Azure services
Target Audience
- Data scientists and ML engineers
- Application developers integrating AI features
- Technical leads and solution architects
